Showing papers on "Quantization (image processing) published in 2001"

The JPEG 2000 still image compression standard

Abstract: One of the aims of the standardization committee has been the development of Part I, which could be used on a royalty- and fee-free basis. This is important for the standard to become widely accepted. The standardization process, which is coordinated by the JTCI/SC29/WG1 of the ISO/IEC has already produced the international standard (IS) for Part I. In this article the structure of Part I of the JPFG 2000 standard is presented and performance comparisons with established standards are reported. This article is intended to serve as a tutorial for the JPEG 2000 standard. The main application areas and their requirements are given. The architecture of the standard follows with the description of the tiling, multicomponent transformations, wavelet transforms, quantization and entropy coding. Some of the most significant features of the standard are presented, such as region-of-interest coding, scalability, visual weighting, error resilience and file format aspects. Finally, some comparative results are reported and the future parts of the standard are discussed.

Distortion-Free Data Embedding for Images

Abstract: One common drawback of virtually all current data embedding methods is the fact that the original image is inevitably distorted by some small amount of noise due to data embedding itself. This distortion typically cannot be removed completely due to quantization, bit-replacement, or truncation at the grayscales 0 and 255. Although the distortion is often quite small, it may not be acceptable for medical imagery (for legal reasons) or for military images inspected under unusual viewing conditions (after filtering or extreme zoom). In this paper, we introduce a general approach for high-capacity data embedding that is distortion-free (or lossless) in the sense that after the embedded information is extracted from the stego-image, we can revert to the exact copy of the original image before the embedding occurred. The new method can be used as a powerful tool to achieve a variety of non-trivial tasks, including distortion-free robust watermarking, distortion-free authentication using fragile watermarks, and steganalysis. The proposed concepts are also extended to lossy image formats, such as the JPG.

Adaptive postfiltering of transform coefficients for the reduction of blocking artifacts

Abstract: This paper proposes a novel postprocessing technique for reducing blocking artifacts in low-bit-rate transform-coded images. The proposed approach works in the transform domain to alleviate the accuracy loss of transform coefficients, which is introduced by the quantization process. The masking effect in the human visual system (HVS) is considered, and an adaptive weighting mechanism is then integrated into the postfiltering. In low-activity areas, since blocking artifacts appear to be perceptually more detectable, a large window is used to efficiently smooth out the artifacts. In order to preserve image details, a small mask, as well as a large central weight, is employed for processing those high-activity blocks, where blocking artifacts are less noticeable due to the masking ability of local background. The quantization constraint is finally applied to the postfiltered coefficients. Experimental results show that the proposed technique provides satisfactory performance as compared to other postfilters in both objective and subjective image quality.

New image compression techniques using multiwavelets and multiwavelet packets

Abstract: Advances in wavelet transforms and quantization methods have produced algorithms capable of surpassing the existing image compression standards like the Joint Photographic Experts Group (JPEG) algorithm. For best performance in image compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry. However, the design possibilities for wavelets are limited because they cannot simultaneously possess all of the desirable properties. The relatively new field of multiwavelets shows promise in obviating some of the limitations of wavelets. Multiwavelets offer more design options and are able to combine several desirable transform features. The few previously published results of multiwavelet-based image compression have mostly fallen short of the performance enjoyed by the current wavelet algorithms. This paper presents new multiwavelet transform and quantization methods and introduces multiwavelet packets. Extensive experimental results demonstrate that our techniques exhibit performance equal to, or in several cases superior to, the current wavelet filters.

Blind watermarking applied to image authentication

Abstract: To prevent image manipulations and fraudulent use of modified images, the embedding of semi-fragile digital watermarks into image data has been proposed. The watermark should survive modifications introduced by random noise or compression, but should not be detectable from non-authentic regions of the image The original image cannot be used by the watermark detector to verify the authenticity of the image. In this paper, we investigate the application of a recently developed quantization based watermarking scheme to image authentication. The watermarking technology, called Scalar Costa Scheme (SCS), allows reliable blind watermark detection from a small number of pixels, and thus enables the detection of local modifications to the image content.

A class of authentication digital watermarks for secure multimedia communication

Abstract: A new approach to digital signatures for imaging, which adapts well to multimedia communications in lossy channels is introduced. Rather than attaching the signature's bit-string as a file-header, it is invisibly etched into the image using a new watermarking algorithm. The watermark is "nonfragile," tolerating small distortions but not malicious tampering aimed at modifying the image's content. In particular, the rank-order relationship in local areas throughout the lowest level of the DWT is exploited to encode the watermark. An edge-based message digest is used. The signature is in the form of binary data and the wavelet decomposition coefficients are modified according to this binary sequence. The signature is also embedded and tested within the SPIHT compression algorithm. The information capacity is studied and the experimental results confirm a logarithm relation between the bit rate and the quantization level, which is similar to the Shannon's capacity theorem. Experiments are performed to examine the signature's transparency and robustness.

Medical image compression based on region of interest, with application to colon CT images

Abstract: CT or MRI medical imaging produce human body pictures in digital form. Since these imaging techniques produce prohibitive amounts of data, compression is necessary for storage and communication purposes. Many current compression schemes provide a very high compression rate but with considerable loss of quality. On the other hand, in some areas in medicine, it may be sufficient to maintain high image quality only in the region of interest, i.e., in diagnostically important regions. This paper discusses a hybrid model of lossless compression in the region of interest, with high-rate, motion-compensated, lossy compression in other regions. We evaluate our method on medical CT images, and show that it outperforms other common compression schemes, such as discrete cosine transform, vector quantization, and principal component analysis. In our experiments, we emphasize CT imaging of the human colon.

Enhancement of JPEG-Compressed Images by Re-application of JPEG

Abstract: A novel method is proposed for post-processing of JPEG-encoded images, in order to reduce coding artifacts and enhance visual quality. Our method simply re-applies JPEG to the shifted versions of the already-compressed image, and forms an average. This approach, despite its simplicity, offers better performance than other known methods, including those based on nonlinear filtering, POCS, and redundant wavelets.

Image distribution system, and image distribution method and program therefor

Abstract: For distributing a user image corresponding to the user position in a virtual space, the invention provides a method of fetching the user image taken with a video camera into the main body of a computer (S 1 ), judging the user position in the virtual space (S 2 ), setting a large quantization coefficient in case of an office view (S 3 ) but setting a small quantization coefficient and an even smaller quantization coefficients for a face area in other cases (S 4 ), then compression encoding the image data with the designated quantization coefficient ((S 5 ) and transferring the image data to a host server apparatus 12 through a network (S 6 ). The user terminal receives images of other users from the host server apparatus (S 7 ), expands the image data (S 8 ) and displays the image data on a display apparatus 44 (S 9 ).

Pipelined Fast 2-D DCT Architecture for JPEG Image Compression

Abstract: This paper presents the architecture and the VHDL design of a Two Dimensional Discrete Cosine Transform (2-D DCT) for JPEG image compression This architecture is used as the core of a JPEG compressor and is the critical path in JPEG compression hardware The 2-D DCT calculation is made using the 2-D DCT separability property, such that the whole architecture is divided into two I-D DCT calculations by using a transpose buffer These parts are described in this paper, with an architectural discussion and the VHDL synthesis results as well The 2-D DCT architecture uses 4,792 logic cells of one Altera Flex10kE FPGA and reaches an operating frequency of 122 MHz One input block with 8/spl times/8 elements of 8 bits each is processed in 252 /spl mu/s and the pipeline latency is 160 clock cycles

Mean-quantization-based fragile watermarking for image authentication

Abstract: The authors propose an image authentication scheme, which is able to detect malicious tampering while tolerating some incidental distortions By modeling the magnitude changes caused by incidental distortion and malicious tampering as Gaussian distributions with small and large variances, respectively, they propose to embed a watermark by using a mean-quantization technique in the wavelet domain The pro- posed scheme is superior to the conventional quantization-based ap- proaches in credibility of authentication Statistical analysis is conducted to show that the probabilities of watermark errors caused by malicious tampering and incidental distortion will be, respectively, maximized and minimized when the new scheme is applied Experimental results dem- onstrate that the credibility of the method is superior to that of the con- ventional quantization-based methods under malicious attack followed by an incidental modification, such as JPEG compression, sharpening or blurring © 2001 Society of Photo-Optical Instrumentation Engineers

Bandwidth scaling of a compressed video stream

Abstract: A method and apparatus for bandwidth scaling of a compressed video stream are disclosed. An original previously compressed video stream image (202) having a first level of compression including a first level of quantization is decompressed, and a set of original motion vectors for each P source picture and for each B source picture is recovered and saved. The decompressed video stream image is re-compressed re-using the most relevant saved original motion vectors in order to create a re-compressed video stream image having a second level of compression including a second level of quantization. The most relevant motion vectors point out to the camera movement and to the moving objects within the original reference frame.

Image capture: simulation of sensor responses from hyperspectral images

Abstract: This paper describes the design and performance of an image capture simulator. The general model underlying the simulator assumes that the image capture device contains multiple classes of sensors with different spectral sensitivities and that each sensor responds in a known way to irradiance over most of its operating range. The input to the simulator is a set of narrow-band images of the scene taken with a custom-designed hyperspectral camera system. The parameters for the simulator are the number of sensor classes, the sensor spectral sensitivities, the noise statistics and number of quantization levels for each sensor class, the spatial arrangement of the sensors and the exposure duration. The output of the simulator is the raw image data that would have been acquired by the simulated image capture device. To test the simulator, we acquired images of the same scene both with the hyperspectral camera and with a calibrated Kodak DCS-200 digital color camera. We used the simulator to predict the DCS-200 output from the hyperspectral data. The agreement between simulated and acquired images validated the image capture response model and our simulator implementation. We believe the simulator will provide a useful tool for understanding the effect of varying the design parameters of an image capture device.

SARI: self-authentication-and-recovery image watermarking system

Abstract: In this project, we designed a novel image authentication system based on a our semi-fragile watermarking technique. The system, called SARI, can accept quantization-based lossy compression to a determined degree without any false alarm and can sensitively detect and locate malicious manipulations. It's the first system that has such capability in distinguishing malicious attacks from acceptable operations. Furthermore, the corrupted area can be approximately recovered by the information hidden in the other part of the contentimage. The amount of information embedded in our SARI system has nearly reached the theoretical maximum zero-error information hiding capacity of digital images. The software prototype includes two parts - the watermark embedder that's freely distributed and the authenticator that can be deployed online as a third-party service or used in the recipient side.

A method of directional filtering for post-processing compressed video

Abstract: A method of post-processing decompressed images includes identification of the direction of an image edge in a pixel block (12) of the image (10) and filtering applied along the boundary of the block in a direction substantially parallel to the detected image edge (22). Pixels are selected for filtering on the basis of the quantization parameter of the block of which they are members, the relative difference between pixels adjacent to the block boundary, and significant changes value of pixels in a filtering segment. Filtering is applied parallel to the detected edge (22) to protect the sharpness of the edge while reducing or eliminating blocking and ringing artifacts. A method of separately post-processing fields of interlaced video eliminating complications arising from separate compression of the fields is also disclosed.

Document compression using rate-distortion optimized segmentation

Abstract: Effective document compression algorithms require that scanned document images be first segmented into regions such as text, pictures, and background. In this paper, we present a multilayer compression algorithm for document images. This compression al- gorithm first segments a scanned document image into different classes, then compresses each class using an algorithm specifically designed for that class. Two algorithms are investigated for seg- menting document images: a direct image segmentation algorithm called the trainable sequential MAP (TSMAP) segmentation algo- rithm, and a rate-distortion optimized segmentation (RDOS) algo- rithm. The RDOS algorithm works in a closed loop fashion by apply- ing each coding method to each region of the document and then selecting the method that yields the best rate-distortion trade-off. Compared with the TSMAP algorithm, the RDOS algorithm can of- ten result in a better rate-distortion trade-off, and produce more ro- bust segmentations by eliminating those misclassifications which can cause severe artifacts. At similar bit rates, the multilayer com- pression algorithm using RDOS can achieve a much higher subjec- tive quality than state-of-the-art compression algorithms, such as DjVu and SPIHT. © 2001 SPIE and IS&T. (DOI: 10.1117/1.1344590)

Quantization Watermarking in the JPEG2000 Coding Pipeline

Abstract: In this paper, we propose a blind watermarking method integrated in the JPEG2000 coding pipeline. Prior to the entropy coding stage, the binary watermark is placed in the independent code-blocks using Quantization Index Modulation (QIM). The quantization strategy allows to embed data in the detail subbands of low resolution as well as in the approximation image. Watermark recovery is performed without reference to the original image during image decompression. The proposed embedding scheme is robust to compression and other image processing attacks. We demonstrate two application scenarios: image authentication and copyright protection.

Perceptual feedback in multigrid motion estimation using an improved DCT quantization

Abstract: In this paper, a multigrid motion compensation video coder based on the current human visual system (HVS) contrast discrimination models is proposed. A novel procedure for the encoding of the prediction errors has been used. This procedure restricts the maximum perceptual distortion in each transform coefficient. This subjective redundancy removal procedure includes the amplitude nonlinearities and some temporal features of human perception. A perceptually weighted control of the adaptive motion estimation algorithm has also been derived from this model. Perceptual feedback in motion estimation ensures a perceptual balance between the motion estimation effort and the redundancy removal process. The results show that this feedback induces a scale-dependent refinement strategy that gives rise to more robust and meaningful motion estimation, which may facilitate higher level sequence interpretation. Perceptually meaningful distortion measures and the reconstructed frames show the subjective improvements of the proposed scheme versus an H.263 scheme with unweighted motion estimation and MPEG-like quantization.

Transcoding apparatus and method

Abstract: A transcoder for transcoding digital video signals includes a decoder and an encoder. In the decoder, an end-of-block (EOB) position of an incoming block received by the decoder is determined and a discrete cosine transform (DCT) block type is determined based on the determined EOB position. A reduced number of DCT coefficients is computed in a subsequent inverse DCT computation based on the DCT block type. In the encoder, if the incoming block is interceded, no DCT coefficients are computed after the EOB of the incoming blocks is performing a DCT. Further, in the encoder when the incoming block is intercoded, an algorithm is applied to predict which DCT coefficients may become zero after a subsequent quantization operation, and only DCT coefficients that may not become zero are computed in performing the DCT.

A computation-distortion optimized framework for efficient DCT-based video coding

Abstract: The rapidly expanding field of multimedia communications has fueled significant research and development work in the area of real-time video encoding. Dedicated hardware solutions have reached maturity and cost-efficient hardware encoders are being developed by several manufacturers. However, software solutions based on a general purpose processor or a programmable digital signal processor (DSP) have significant merits. Toward this objective, we have developed a flexible framework for video encoding that yields very good computation-performance tradeoffs. The proposed framework consists of a set of optimized core components: motion estimation (ME), the discrete cosine transform (DCT), quantization, and mode selection. Each of the components can be configured to achieve a desired computation-performance tradeoff. The components can be assembled to obtain encoders with varying degrees of computational complexity. Computation control has been implemented within the proposed framework to allow the resulting algorithms to adapt to the available computational resources. The proposed framework was applied to MPEG-2 and H.263 encoding using Intel's Pentium/MMX desktop processor. Excellent speed-performance tradeoffs were obtained.

Apparatus and method for compressing and decompressing image files

Abstract: An apparatus and method for compressing and decompressing digital image files is described. At the image encoder/compressor, an input image file, which may be of bilevel, grayscale, or color file type, is subdivided into one or more sub-images. Each sub-image may be separately compressed. In the case of grayscale or color input images, the input image may be pre-processed using a threshold parameter to quantize the intensity and/or color vectors into a compressed palette of intensities and/or color vectors. A forward transform is performed on each pre-processed sub-image, based on a binary quincunx image pyramid and a set of pixel value prediction equations. The output of the forward transform comprises a set of prediction error signals and a coarse low-band signal. Each of the prediction error signals and the coarse low-band signal are run length and/or tree encoded, and all of the outputs of the run length and/or tree encoders are combined into a single array, which is encoded using a Huffman coding algorithm or arithmetic algorithm. The output of the Huffman encoder or its equivalent is written to a compressed output file in a format conducive to image reconstruction at the image decompressor. The compressed output file is stored and/or transmitted to an image decoder/decompressor. At the image decoder/decompressor, the encoding/compression process is reversed to generate a decompressed image file, which may be stored and/or displayed as appropriate. Embodiments of the system may implement either lossless compression or lossy compression, where lossiness may be due to transmission of fewer pixels than those present in the original image and/or by quantization of the pixel intensities and/or color vectors into fewer intensity/color levels than those present in the original image.

On the architecture and performance of a hybrid image rejection receiver

Abstract: This paper describes a hybrid image rejection receiver. The hybrid image rejection receiver contains a modified Hartley (1928) image rejection mixer and a digital image rejection processor. The modified Hartley image rejection mixer performs similarly to an original Hartley image rejection receiver but provides two digital outputs. In one output it enhances the desired signal and in the other output it enhances the image signal. The digital image rejection processor first measures the mismatching effect in the analog devices and then suppresses the image signal by compensating for the mismatching effect. We also propose a simplified implementation method for the hybrid image rejection receiver to reduce its computation complexity. Computer simulation was used to evaluate the performance of this simplified implementation method to include the quantization effect introduced by the A/D converters. Simulation results show that the proposed hybrid image rejection receiver achieves much better performance than the original Hartley image rejection receiver. This architecture greatly relaxes the matching requirements of the analog devices and has a low complexity for an IC implementation.

The choice of watermark domain in the presence of compression

Abstract: We determine the watermark domain that maximizes data hiding capacity. We focus on the situation in which the watermarked signal undergoes lossy compression involving quantization in a specified compression domain. A novel linear model for the process of quantization is proposed which leads to analytical results estimating the data hiding capacity for various watermarking domains. Using this framework we predict appropriate transforms for robust spread spectrum data hiding in the face of JPEG compression. Simulation results verify our theoretical observations. We find that a repetition code used in conjunction with spread spectrum watermarking in a different domain than employed for compression improves data hiding capacity.

Data hiding technique in JPEG compressed domain

Abstract: JPEG is a common image format in the world wide web. JPEG-compressed images can be used to hide data for secret internet communication and simply any auxiliary data. In this paper, we propose an algorithm called J-Mark to embed invisible watermark information into JPEG compressed images in the compress domain. There are three parts of J-Mark: block selection, DCT coefficient selection, and modification of selected DCT coefficients. Only the texture blocks with significant masking properties are selected in block selection. Only the DCT coefficients with significant energy in the selected blocks are selected. The watermark data are embedded as the 'randomized parity' in the selected DCT coefficients. The embedded data can be recovered perfectly in the compressed domain without fully decoding the JPEG image. Experiment results suggest that the proposed J-Mark can hide the watermarking data without detectable visual artifacts. Although the data hiding capacity differs among images, some parameter of J-Mark can be used to achieve tradeoff between data hiding capacity and visual quality.

A novel approach for increasing security and data embedding capacity in images for data hiding applications

Abstract: Data hiding in multimedia is the process of secretly embedding information into data sources such as image, video, or audio signals without changing the perceptual quality of the data source. We present a novel blind data hiding technique for hiding information in still images. This technique is based on embedding the information in the transform domain, after decorrelating the samples in the spatial domain. This results in a significant increase in the number of transform coefficients that can be used to transmit the hidden information. The technique is suitable for a variety of data hiding applications such as steganography, data authentication and captioning. The technique achieves a higher and more secure data embedding rate than existing data embedding transform domain techniques developed for these particular applications.

Psychovisual and statistical optimization of quantization tables for DCT compression engines

Abstract: The paper presents a new and statistically robust algorithm able to improve the performance of the standard DCT compression algorithm for both perceived quality and compression size. The approach proposed combines together an information theoretical/statistical approach with HVS (human visual system) response functions. The methodology applied permits us to obtain a suitable quantization table for specific classes of images and specific viewing conditions. The paper presents a case study where the right parameters are learned after an extensive experimental phase, for three specific classes: document, landscape and portrait. The results show both perceptive and measured (in term of PSNR) improvement. A further application shows how it is possible obtain significant improvement profiling the relative DCT error inside the pipeline of images acquired by typical digital sensors.

Secure blind image steganographic technique using discrete Fourier transformation

Abstract: We present a new steganographic technique for covert communications. The technique embeds the hidden information in the DFT domain after permuting the image pixels in the spatial domain using a key. The permutation process introduces randomness into the cover image and results in a significant increase in the number of transform coefficients that can be used to transmit the hidden information. The hidden information is embedded using a quantization technique. The perceptual and statistical properties of the cover and the stego images remain similar for small quantization steps. The security of the system is examined against known stego attack.

A multistage perceptual quality assessment for compressed digital angiogram images

Abstract: This paper describes a multistage perceptual quality assessment (MPQA) model for compressed images. The motivation for the development of a perceptual quality assessment is to measure (in)visible differences between original and processed images. The MPQA produces visible distortion maps and quantitative error measures informed by considerations of the human visual system (HVS). Original and decompressed images are decomposed into different spatial frequency bands and orientations modeling the human cortex. Contrast errors are calculated for each frequency and orientation, and masked as a function of contrast sensitivity and background uncertainty. Spatially masked contrast error measurements are then made across frequency bands and orientations to produce a single perceptual distortion visibility map (PDVM). A perceptual quality rating (PQR) is calculated from the PDVM and transformed into a one to five scale, PQR/sub 1-5/, for direct comparison with the mean opinion score, generally used in subjective ratings. The proposed MPQA model is based on existing perceptual quality assessment models, while it is differentiated by the inclusion of contrast masking as a function of background uncertainty. A pilot study of clinical experiments on wavelet-compressed digital angiogram has been performed on a sample set of angiogram images to identify diagnostically acceptable reconstruction. Our results show that the PQR/sub 1-5/ of diagnostically acceptable lossy image reconstructions have better agreement with cardiologists' responses than objective error measurement methods, such as peak signal-to-noise ratio. A Perceptual thresholding and CSF-based Uniform quantization (PCU) method is also proposed using the vision models presented in this paper. The vision models are implemented in the thresholding and quantization stages of a compression algorithm and shown to produce improved compression ratio performance with less visible distortion than that of the embedded zerotrees wavelet (EZWs).

An efficient use of MPEG-4 FAP interpolation for facial animation at 70 bits/frame

Abstract: An efficient algorithm is proposed to exploit the facial animation parameter (FAP) interpolation modality specified by the MPEG-4 standard in order to allow very low bit-rate transmission of the animation parameters. The proposed algorithm is based on a comprehensive analysis of the cross-correlation properties that characterize FAPs, which is here reported and discussed extensively. Based on this analysis, a subset of ten almost independent FAPs has been selected from the full set of 66 low-level FAPs to be transmitted and used at the decoder to interpolate the remaining ones. The performance achievable through the proposed algorithm have been evaluated objectively by means of conventional PSNR measures and compared to an alternative solution based on the increase of the quantization scale factor used for FAP encoding. The subjective evaluation and comparison of the results has also been made possible by uploading mpg movies on a freely accessible Web site. Experimental results demonstrate that the proposed FAP interpolation algorithm allows efficient parameter encoding at around 70 bits/frame or, in other words, at less than 2 kbits/s for smooth synthetic video at 25 frames/s.